Biological structure and function emerge from scaling unsupervised learning to 250 million protein sequences

Alexander Rives; Joshua Meier; Tom Sercu; Siddharth Goyal; Zeming Lin; Jason Liu; Demi Guo; Myle Ott; C. Lawrence Zitnick; Jerry Ma; Rob Fergus

doi:10.1101/622803

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Biological structure and function emerge from scaling unsupervised learning to 250 million protein sequences

Alexander Rives, Joshua Meier, Tom Sercu, Siddharth Goyal, Zeming Lin, Jason Liu, Demi Guo, Myle Ott, C. Lawrence Zitnick, Jerry Ma, Rob Fergus

doi: https://doi.org/10.1101/622803

Alexander Rives

1Facebook AI Research

2Dept. of Computer Science, New York University

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For correspondence: arives@cs.nyu.edu

Joshua Meier

1Facebook AI Research

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Tom Sercu

1Facebook AI Research

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Siddharth Goyal

1Facebook AI Research

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Zeming Lin

2Dept. of Computer Science, New York University

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Jason Liu

1Facebook AI Research

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Demi Guo

3Harvard University

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Myle Ott

1Facebook AI Research

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C. Lawrence Zitnick

1Facebook AI Research

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Jerry Ma

4Booth School of Business, University of Chicago & Yale Law School

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Rob Fergus

2Dept. of Computer Science, New York University

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Biological structure and function emerge from scaling unsupervised learning to 250 million protein sequences

Alexander Rives, Joshua Meier, Tom Sercu, Siddharth Goyal, Zeming Lin, Jason Liu, Demi Guo, Myle Ott, C. Lawrence Zitnick, Jerry Ma, Rob Fergus

bioRxiv 622803; doi: https://doi.org/10.1101/622803

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Biological structure and function emerge from scaling unsupervised learning to 250 million protein sequences

Alexander Rives, Joshua Meier, Tom Sercu, Siddharth Goyal, Zeming Lin, Jason Liu, Demi Guo, Myle Ott, C. Lawrence Zitnick, Jerry Ma, Rob Fergus

bioRxiv 622803; doi: https://doi.org/10.1101/622803

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